Total 50,528 skills, AI & Machine Learning has 8482 skills
Showing 12 of 8482 skills
[QianWen] Generate and edit images using Wan and Qwen Image models. Supports text-to-image, image editing (style transfer, subject consistency, text rendering), and interleaved text-image output. TRIGGER when: user wants to create illustrations, product images, artistic designs, posters, text-to-image generation, edit/transform existing images, apply style transfer, generate images based on reference photos, interleaved text-image content, mentions Wan/Qwen Image models/AI art creation, or explicitly invokes this skill by name (e.g. use qianwen-image-generation). DO NOT TRIGGER when: user wants to understand/analyze existing images or OCR (use qianwen-vision), video generation (use qianwen-video-generation), text-only tasks.
Use the local `5dive` CLI on a 5dive runtime VM to spawn, inspect, send to, and tear down sibling agents. Trigger this skill whenever the user asks for a worker, sub-agent, side task, parallel run, "another agent", "fan out", "delegate", or anything that needs more than one Claude/Codex/Gemini process running at once on the host. Also trigger when the user asks to inspect, restart, or pair an existing agent, when they mention `/var/lib/5dive/`, or when they need a machine-readable health check (`5dive doctor --json`). Always prefer `5dive` over running coding CLIs by hand — it is the only sanctioned way to keep agents under systemd.
BYOK — register a custom LLM endpoint (Anthropic, OpenAI, Qwen, DeepSeek, etc.) with your own API key
Run Claude Code CLI, VS Code, or JetBrains ACP through a local proxy that routes to NVIDIA NIM, Kimi, OpenRouter, DeepSeek, or local LLMs
Modo de explicação em camadas. Aplica SOMENTE na resposta imediatamente após a invocação — depois volta ao normal automaticamente. A resposta deve ser em manchete (1 frase, no máximo 2), no nível exato da granularidade da pergunta. Não listar itens individuais quando a pergunta foi sobre o conjunto. Não oferecer drill-down nem perguntar se quer detalhar — esperar o usuário pedir. Use SOMENTE quando o usuário invocar explicitamente com "/peel-talk", "peel-talk", "explica no peel-talk", "peel talk", "modo peel", ou variações. NÃO invocar automaticamente em outras tarefas.
Guide for using the Pinecone CLI (pc) to manage Pinecone resources from the terminal. The CLI supports ALL index types (standard, integrated, sparse) and all vector operations — unlike the MCP which only supports integrated indexes. Use for batch operations, vector management, backups, namespaces, CI/CD automation, and full control over Pinecone resources.
Show a dashboard of all projects in the Claude Brain graph. Triggers: "brain status", "show projects", "show brain", "what's in my brain", "project dashboard", "brain overview", "list projects", "summary". Don't fire for loads (use brain-load) or saves (use brain-save).
Botpress integration. Manage Bots. Use when the user wants to interact with Botpress data.
Orchestrates implementation of a plan file by delegating work to subagents in parallel. Verifies git branch state, tracks progress, and ensures high-quality implementation. Invoke with a plan file path and optional model override: /implement plans/my-plan.md [--model sonnet]
Dispatches many independent items in parallel: create a table, fan out to subagents, aggregate results. One row = one unit of work.
MoveIt2 SRDF generation, validation, and planning-semantics workflow. Use when creating, editing, regenerating, inspecting, or validating `.srdf` files, `gen_srdf()` sources, MoveIt planning groups, virtual joints, passive joints, end effectors, group states, disabled collisions, URDF-linked planning semantics, or SRDF handoff to CAD Explorer review. Use the URDF skill for robot structure, the SDF skill for simulator descriptions, and the render skill for rendering, Explorer links, and optional MoveIt2 controls.
Use when an SGLang, vLLM, or TensorRT-LLM serving/model optimization task needs prior model-family PR evidence. Query and read the PR-driven history docs under model-pr-optimization-history before choosing source paths, fast paths, kernel/fusion ideas, regression risks, or validation lanes.